: Background Clustering algorithms are widely used in the analysis of microarray data. In clinical studies, they are often applied to find groups of co-regulated genes. Clustering...
Background: The decrease in cost for sequencing and improvement in technologies has made it easier and more common for the re-sequencing of large genomes as well as parallel seque...
Being able to clearly visualize clusters of genes provided by gene expressions over a set of samples is of high importance. It gives researchers the ability to create an image of t...
: Biomedical data sets often have mixed categorical and numerical types, where the former represent semantic information on the objects and the latter represent experimental result...
Gene expression profiles with clinical outcome data enable monitoring of disease progression and prediction of patient survival at the molecular level. We present a new computatio...